About this Course
최근 조회 23,070

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

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일정에 따라 마감일을 재설정합니다.

완료하는 데 약 56시간 필요

권장: 7 hours/week...

영어

자막: 영어

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

완료하는 데 약 56시간 필요

권장: 7 hours/week...

영어

자막: 영어

강의 계획 - 이 강좌에서 배울 내용

1
완료하는 데 1시간 필요

Course Orientation

You will become familiar with the course, your classmates, and our learning environment. The orientation will also help you obtain the technical skills required for the course.

...
2 videos (Total 8 min), 4 readings, 1 quiz
4개의 읽기 자료
Syllabus10m
About the Discussion Forums10m
Updating Your Profile10m
Social Media10m
1개 연습문제
Orientation Quiz10m
완료하는 데 8시간 필요

Module 1: Foundations

This module serves as the introduction to the course content and the course Jupyter server, where you will run your analytics scripts. First, you will read about specific examples of how analytics is being employed by Accounting firms. Next, you will learn about the capabilities of the course Jupyter server, and how to create, edit, and run notebooks on the course server. After this, you will learn how to write Markdown formatted documents, which is an easy way to quickly write formatted text, including descriptive text inside a course notebook. Finally, you will begin learning about Python, the programming language used in this course for data analytics.

...
5 videos (Total 29 min), 2 readings, 2 quizzes
2개의 읽기 자료
Module 1 Overview10m
Lesson 1-1 Readings10m
1개 연습문제
Module 1 Graded Quiz20m
2
완료하는 데 8시간 필요

Module 2: Introduction to Python

This module focuses on the basic features in the Python programming language that underlie most data analytics scripts. First, you will read about why accounting students should learn to write computer programs. Second, you will learn about basic data structures commonly used in Python programs. Third, you will learn how to write functions, which can be repeatedly called, in Python, and how to use them effectively in your own programs. Finally, you will learn how to control the execution process of your Python program by using conditional statements and looping constructs. At the conclusion of this module, you will be able to write Python scripts to perform basic data analytic tasks.

...
5 videos (Total 29 min), 2 readings, 2 quizzes
5개의 동영상
Introduction to Python Functions5m
Python Programming Concepts6m
2개의 읽기 자료
Module 2 Overview10m
Lesson 2-1 Readings10m
1개 연습문제
Module 2 Graded Quiz20m
3
완료하는 데 8시간 필요

Module 3: Introduction to Data Analysis

This module introduces fundamental concepts in data analysis. First, you will read a report from the Association of Accountants and Financial Professionals in Business that explores Big Data in Accountancy. Next, you will learn about the Unix file system, which is the operating system used for most big data processing (as well as Linux and Mac OSX desktops and many mobile phones). Second, you will learn how to read and write data to a file from within a Python program. Finally, you will learn about the Pandas Python module that can simplify many challenging data analysis tasks, and includes the DataFrame, which programmatically mimics many of the features of a traditional spreadsheet.

...
5 videos (Total 29 min), 2 readings, 2 quizzes
5개의 동영상
Python File I/O7m
Introduction to Pandas6m
2개의 읽기 자료
Module 3 Overview10m
Lesson 3-1 Readings10m
1개 연습문제
Module 3 Graded Quiz20m
4
완료하는 데 8시간 필요

Module 4: Statistical Data Analysis

This module introduces fundamental concepts in data analysis. First, you will read about how to perform many basic tasks in Excel by using the Pandas module in Python. Second, you will learn about the Numpy module, which provides support for fast numerical operations within Python. This module will focus on using Numpy with one-dimensional data (i.e., vectors or 1-D arrays), but a later module will explore using Numpy for higher-dimensional data. Third, you will learn about descriptive statistics, which can be used to characterize a data set by using a few specific measurements. Finally, you will learn about advanced functionality within the Pandas module including masking, grouping, stacking, and pivot tables.

...
5 videos (Total 33 min), 2 readings, 2 quizzes
5개의 동영상
Introduction to Descriptive Statistics10m
Advanced Pandas8m
2개의 읽기 자료
Module 4 Overview10m
Lesson 4-1 Readings10m
1개 연습문제
Module 4 Graded Quiz20m

강사

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Robert Brunner

Professor
Accountancy

Start working towards your Master's degree

이 강좌은(는) 일리노이대학교 어버너-섐페인캠퍼스의 100% 온라인 Master of Science in Accountancy (iMSA) 중 일부입니다. 전체 프로그램을 수료하면 귀하의 강좌가 학위 취득에 반영됩니다.

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